Shallow Thoughts : : Nov

Sewing Project: Saving my Toes

I have a platform bed, which means the bottom part is made of wood with drawers in it (I'm not clear why this style is called "platform"). Having the drawer space is handy, but it has one big drawback: it means there's a wood corner right where I'm likely to kick it accidentally in the dark on a nocturnal get-up. I've done this enough times that I'm amazed I haven't broken a toe yet, and I've long been sure it's going to happen some day (especially as I get older and my bones get more brittle).

I've been having a lot of fun at the monthly Sewing Meetup at Los Alamos Makers, and really enjoying it. I've fixed up lots of too-large clothes from thrift shops and tech conferences, and made projects like a purse, padded phone cases, and a a cushion for an aging dining table chair.

So when Jodi, the meetup leader, mentioned that she was bringing a bag of stuffing and wanted to make some sofa pillows, I thought: I don't really need any more sofa pillows ... but I can think of a place where I need some cushions!

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Finding the Bounding Box of a Dataset

Yesterday I wrote about PyTopo's difficulty in displaying a large all-US dam dataset. I've finally fixed the bug ... though it's still very slow to display the whole dataset: you have to wait a minute or more to redrew if it's zoomed all the way out to show the whole world.

Wait, the whole world? I thought this dataset was for all dams in the US?

Yes, in theory. In practice, not so much.

(I'm going to cheat a little bit and call this 30 Day Map Challenge Day 3: Polygons, because a bounding box is a polygon and I've spent so much time on this that I definitely don't have time to do any other 30 day projects today.)

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Plotting Dams (30 Day Map Challenge Day 1: Points) and a PyTopo Tweak

The 30 Day Map Challenge started yesterday, and already I'm a day behind. (I'm not going to try to keep up; I'll be sporadic about challenge entries.) Day 1 was Points.

The website for the challenge has an interesting list of possible data sources, and clicking around them, I found one that looked like a good quickie: a Data is Plural entry that mentioned a dataset from the National Inventory of Dams that lists all dams in the US. That sounds like a useful thing to have.

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